New computational method for identifying drug targets

New computational methods for medicinal clinical trials can speed up drug discovery.

Biplab Das

A Saudi Arabia research team has discovered a computational method that can identify new targets and off-targets for drugs.

Besides developing new drugs, knowledge of off-targets can help reduce drug resistance and failure of new drugs in clinical trials.

Xin Gao and his colleagues from King Abdullah University of Science and Technology (KAUST) developed a method called integrated structure- and system-based approach of drug-target prediction (iDTP). This method with average specificity of 81% identified new and known targets of drugs and metabolites by integrating structural signatures of small molecules with their tissue-specific expression profiles1.

To assess the drug-discovery potential of iDTP, Gao’s team used this method to predict all known targets for 11 experimental drugs. Using in vitro drug-binding studies, they then predicted two novel target proteins for coenzyme A (CoA): peroxisome proliferator-activated receptor gamma (PPARG) and B-cell lymphoma 2 (Bcl-2).

These target proteins (PPARG and Bcl-2) were experimentally validated by Stefan Arold from KAUST and William Bourguet from France-based Centre de Biochimie Structurale.

The researchers say that the affinity of CoA for Bcl-2, an important oncogenic protein, illustrates how the method could be used for drug discovery by suggesting possible lead compounds.

This method could also provide insight into the binding mechanisms of known drugs for which the drug–target complex is unknown, they say.

“Besides aiding drug discovery, this method would be useful for predicting possible targets for chemical pollutants such as bisphenols,” says Gao.